Quantum Computing (QC) has become an interdisciplinary and fast-developing field, with a lot of interest shown by both the academic and industrial community because of its essentially new paradigm of information processing and outstanding capabilities of the quantum computer based on its innovation and a complete break with the paradigm of non-quantum computing. Although this is the future of this potential, there is very little that is known of its transformative effect in the health industry. The survey is the first attempt to give a systematic and broad overview of how quantum computing can improve healthcare, especially in compute-intensive applications like optimization of operations, medical imaging, DNA sequencing, personalized medicine, and drug discovery. The concepts covered in this chapter are comprised of foundational concepts, enabling technologies, areas of applications, system requirements, and architectural models, security, unresolved challenges and imminent research directions. This chapter takes into consideration the general outlook on the quantum computing's significance in medicine and also serves as an efficient guide for new researchers or well-established ones looking into the area. It tries to bring light into the existing research environment, point out the prospects and the challenges and achieve the guidance of the design of future quantum-driven healthcare architectures and applications.
Quantum Computing (QC) has become an interdisciplinary and fast-developing field, with a lot of interest shown by both the academic and industrial community because of its essentially new paradigm of information processing and outstanding capabilities of the quantum computer based on its innovation and a complete break with the paradigm of non-quantum computing. Although this is the future of this potential, there is very little that is known of its transformative effect in the health industry. The survey is the first attempt to give a systematic and broad overview of how quantum computing can improve healthcare, especially in compute-intensive applications like optimization of operations, medical imaging, DNA sequencing, personalized medicine, and drug discovery. The concepts covered in this chapter are comprised of foundational concepts, enabling technologies, areas of applications, system requirements, and architectural models, security, unresolved challenges and imminent research directions. This chapter takes into consideration the general outlook on the quantum computing's significance in medicine and also serves as an efficient guide for new researchers or well-established ones looking into the area. It tries to bring light into the existing research environment, point out the prospects and the challenges and achieve the guidance of the design of future quantum-driven healthcare architectures and applications.
In recent years, the interdisciplinary field of quantum computing has rapidly developed and garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to hitherto unattainable computational capabilities. However, despite its potential, the full extent of quantum computing’s impact on healthcare remains largely unexplored. This survey paper presents the first systematic analysis of the various capabilities of quantum computing in enhancing healthcare systems, with a focus on its potential to revolutionize compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization. Through a comprehensive analysis of existing literature, we have developed taxonomies across different dimensions, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, providing a panoramic view of the quantum computing paradigm for healthcare. Our survey aims to aid both new and experienced researchers in quantum computing and healthcare by helping them understand the current research landscape, identifying potential opportunities and challenges, and making informed decisions when designing new architectures and applications for quantum computing in healthcare.
The use of quantum computing1 in healthcare represents a significant shift with the potential to revolutionize medical research, diagnostics, and treatment. Quantum computing can process and analyze large datasets much faster than classical computing, offering new opportunities in healthcare. This paper examines the various ways quantum computing can be applied in healthcare, such as in drug discovery, genetic research, personalized medicine, and complex disease modeling. By using quantum algorithms, researchers can identify new treatment targets and simulate the effects of drugs on human biology in ways that were previously impossible, which can reduce the time and cost of bringing new drugs to market. Quantum computing also allows for analyzing large genomic datasets2, which can help tailor treatments to individual genetic profiles. Additionally, this technology helps in modeling complex biological systems and disease processes, providing insights into the mechanisms of diseases at a molecular level and enabling the development of more effective treatments. However, integrating quantum computing into healthcare comes with challenges such as technical limitations, the need for specialized expertise, data security concerns, and ethical considerations. This paper provides a comprehensive overview of the potential applications of quantum computing in healthcare, addresses the associated challenges, and discusses the future directions of this growing field, emphasizing the importance of interdisciplinary collaboration in fully utilizing quantum technologies in medicine. In recent years, quantum computing has rapidly advanced and attracted significant interest from academia and industry due to its unique ability to process information differently, resulting in previously unattainable computational capabilities. Despite its potential, the full impact of quantum computing on healthcare has not been thoroughly explored. This survey paper provides a systematic analysis of quantum computing's various capabilities in improving healthcare systems, focusing on its potential to transform compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing4, medical imaging5, and operational optimization. Through a comprehensive review of existing literature, we have developed taxonomies6 covering different aspects, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, offering a comprehensive view of the quantum computing paradigm for healthcare. Our survey aims to assist new and experienced researchers in quantum computing and healthcare by helping them comprehend the current research landscape, identify potential opportunities and challenges, and make informed decisions when developing new architectures and applications for quantum computing in healthcare
The interdisciplinary field of quantum computing has garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to cutting-edge computational capabilities.However, despite its potential, the full extent of quantum computing's impact on healthcare remains largely unexplored.This white paper explores the first systematic analysis of the various capabilities of quantum computing in enhancing healthcare systems, with a focus on its potential to revolutionize compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization thus, providing a panoramic view of the quantum computing[1] paradigm for healthcare.
Quantum computing, an interdisciplinary area that processes data in fundamentally different ways, has recently grown and attracted a lot of attention from academics and businesses alike because of its potential to achieve computational powers that were previously unimaginable. Quantum computing's potential in the medical field has not been thoroughly explored as yet. Computing at the quantum level has the potential to revolutionize computationally intensive healthcare applications such as personalized medicine, drug discovery, medical imaging, DNA sequencing, and operational optimization. This review article provides the first all- encompassing examination of the many applications of quantum computing to healthcare systems, focusing on these specific domains. Many different areas are covered by our taxonomies, such as foundational and enabling technologies, applications, needs, architectures, security, open problems, and potential avenues for future study. The outcome of this thorough literature study is an all-encompassing perspective on the quantum computing paradigm as it pertains to healthcare. Synthetic intelligence (AI) and quantum computing are about to converge, and this article delves into how that can change the face of healthcare. In this study, we take a look at how quantum physics might help us understand how to improve AI for faster drug development, more precise clinical diagnostics, and more tailored treatment plans. The investigation probes the means by which molecular-level quantum simulations can represent complicated organic processes, enabling the unprecedented prediction of treatment interactions and the design of medicine. Also covered in the article is the idea of using quantum sensors in conjunction with AI to provide better clinical imaging that can pick up on more widespread problems. Highlighting its role in bringing in a new technology of personalized medicinal drug and efficient drug improvement, this synergy is discussed for its transformational power.
Quantum computing (QC) represents a paradigm shift in computational power, offering unique capabilities for addressing complex problems that are infeasible for classical computers. This review paper provides a detailed account of the current state of QC, with a particular focus on its applications within medicine. It explores fundamental concepts such as qubits, superposition, and entanglement, as well as the evolution of QC from theoretical foundations to practical advancements. The paper covers significant milestones where QC has intersected with medical research, including breakthroughs in drug discovery, molecular modeling, genomics, and medical diagnostics. Additionally, key quantum techniques such as quantum algorithms, quantum machine learning (QML), and quantum-enhanced imaging are explained, highlighting their relevance in healthcare. The paper also addresses challenges in the field, including hardware limitations, scalability, and integration within clinical environments. Looking forward, the paper discusses the potential for quantum-classical hybrid systems and emerging innovations in quantum hardware, suggesting how these advancements may accelerate the adoption of QC in medical research and clinical practice. By synthesizing reliable knowledge and presenting it through a comprehensive lens, this paper serves as a valuable reference for researchers interested in the transformative potential of QC in medicine.
Conventional treatment methods make even the most basic healthcare issues more complicated, which in turn increases the number of parties involved. Classical computing lacks the speed and accuracy needed for effective stakeholder collaboration in COVID-19 healthcare solutions, such as patients, insurance agents, healthcare practitioners, pharmaceutical suppliers, etc. The research uses organizational information processing theory (OIPT) to examine how quantum computing which is applications of artificial intelligence (AI) could transform the healthcare business, creating a more sustainable and less burdened system. The study of quantum computing (QC) has the potential to bring about “quantum leaps,” which might have unforeseen consequences for healthcare. The discovery of new medications, the personalization of medicinal treatments, and the acceleration of DNA sequencing are just a few of the many possible applications of this method. The potential of QC to transform compute-intensive healthcare tasks like drug-discovery, personalized-medicine, DNA-sequencing, medical-imaging, and operational-optimization is the primary focus of this survey paper, which offers the first comprehensive analysis of QCs diverse capabilities in improving healthcare systems. After a thorough literature study, we created taxonomies on the healthcare QC paradigm’s history and supporting technologies, applications, needs, architectures, security, outstanding questions, and future research prospects. We hope that by conducting this survey, researchers with varying levels of experience in quantum computing and healthcare will better understand the state of the art, assess opportunities and threats, and make informed decisions as they develop novel architectures and applications for this emerging field.